By Geoff LeFevre
Token ecosystem creation requires a phased strategic process in order to navigate its complexities. To learn more about our full process for token ecosystem creation, please download the full report here.
Tokens are value creation and exchange mechanisms that allow network agents to participate in, and/or manage the system. They ensure that nodes operate effectively and actors participate in a coordinated manner. Therefore, they play an important role in aligning the incentives of the ecosystem participants. A token ecosystem is a highly complex system designed to deliver a socially and economically optimal allocation of resources. It is this complexity that requires structured top-down thinking in order to clearly organize and prioritize an integrated set of challenges. It is critical to deconstruct these challenges into the singular primary problem that is to become the goal of the token economy and define the constraints of this problem.
Whether you are a start-up or a corporation, understanding this new emerging business model and how it can add value to your organization should be a key priority. However, actually getting to the core problem can be very difficult. When examining your particular use case, it is too easy to race through problem structuring and jump right into mapping out your system and ideating potential solutions and mechanisms. This mistake can lead to inefficient product feature prioritization, and even worse, can lead to misalignment later in the design process when team members work against each other trying to solve different problems. In fact, most issues we see emerge in the token design process are due to the fact that token teams did not take the time required to properly frame their problem and develop a universal agreement of the core problems they are actually trying to solve.
This kind of problem-solving demands the ability to see a problem from multiple perspectives even though they may challenge our initial assumptions, pre-conditioned beliefs, and experiences. Second, it is important for us to be able to navigate through complexity to find the essence of the problem and identify linkages to its sub-issues. A good method of problem-solving for complex issues is the MECE approach, established by McKinsey & Co:
Good logic trees follow MECE: mutually exclusive, collectively exhaustive. This means that issues should be mutually exclusive, or said another way, without overlap. Collectively exhaustive means that all issues are covered and there are no gaps. To do this requires root cause thinking. To get problems well-structured is very challenging and takes considerable thinking, and requires high degrees of collaboration. For complex problems, it is not uncommon to have overlap between identified problems, and although this should be avoided or minimised as much as possible, it is absolutely critical that the identified problem set is completely exhaustive, meaning all aspects are being considered and there are no gaps in your analysis. One extremely useful outcome of problem structuring is that since each branch is mutually exclusive (or as exclusive as possible), each branch can be treated independently of each other when exploring your solution space. We’ll discuss some benefits of this with examples below:
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A clear problem definition can be achieved by using the Problem Statement Worksheet (shown below) which helps define the core problem by posing a critical question that needs to be answered whilst laying out the context, criteria for success, the scope of solution space, and various stakeholders and constraints that need to be satisfied.
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Problem Structuring Applications
Network governance attempts to solve the problem of who needs to make decisions and when. When approached from the perspective of the entire network the issue of governance becomes so complex that it seems unlikely that there is a single governance solution. This is not a new problem, and human beings have been trying to solve this for millennia. But what if you didn’t need a single governance solution to scale to all issues? Problem structuring breaks a problem into branches that can be treated independently. Breaking down and structuring a problem in this way can help take the global problem of network governance, and apply it locally. By creating a set of mutually exclusive problems and compartmentalising them, solutions can be tailored to those specific problems that require governance solutions, and not those where it is not required, or where another governance solution is required. Not every issue requires a vote, and not everyone needs to involved in every vote. By starting off with a well defined and structured problem you can start to identify specifically where governance is required and how it should it applied.
AI & Machine Learning
This framework can even be used as a framework when deciding which types of machine learning models should be applied to streamline or optimise network operations. By breaking a global problem into smaller local problems that can be treated independently, AI & ML solutions can be catered specifically to each sub-problem. For example, if a sub-problem requires explainability, neural networks are probably a bad choice, instead, a model such as decision trees could be used. Likewise, if accuracy is a local priority over explainability than neural nets could potentially be a good choice, and decision tree models should be avoided. Again by breaking a problem into mutually exclusive components helps you find better solutions.
Token and Mechanism Design
Once you have your problem organised and your team on the same page, design choices and feature prioritization in later phases becomes a relatively smooth process. By breaking the problem into mutually exclusive sub-problems each one can be treated independently and mechanisms can be tailored to a specific problem. Perhaps you don’t even need a token to solve your problem! Or maybe a token is only required in a subset of your network to incentive ledger maintenance, and not required in the market layer to access the good or service provided by the network.
Problem structuring is only the beginning of the token design process so make sure you set a strong foundation early on and spend the time to structure your problem properly and identify all potential subproblems with as little overlap as possible.
To learn more about our phased strategic process for token ecosystem creation, please download the full report download the full report:
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